Add Javascript (WebAssembly) API for Dolphin CTC models (#2093)

@@ -9,6 +9,13 @@ git status
 ls -lh
 ls -lh node_modules
 
+# asr with offline dolphin ctc
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+tar xvf sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+rm sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+node ./test-offline-dolphin-ctc.js
+rm -rf sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02
+
 # speech enhancement
 curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speech-enhancement-models/gtcrn_simple.onnx
 curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/speech-enhancement-models/inp_16k.wav
@@ -56,7 +63,7 @@ curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/m
 tar xvf matcha-icefall-en_US-ljspeech.tar.bz2
 rm matcha-icefall-en_US-ljspeech.tar.bz2
 
-wget https://github.com/k2-fsa/sherpa-onnx/releases/download/vocoder-models/vocos-22khz-univ.onnx
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/vocoder-models/vocos-22khz-univ.onnx
 
 node ./test-offline-tts-matcha-en.js
 

@@ -21,8 +21,8 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest]
-        total: ["8"]
-        index: ["0", "1", "2", "3", "4", "5", "6", "7"]
+        total: ["11"]
+        index: ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10"]
 
     steps:
       - uses: actions/checkout@v4

@@ -119,6 +119,7 @@ We also have spaces built using WebAssembly. They are listed below:
 |VAD + speech recognition (Chinese 多种方言) with a [TeleSpeech-ASR][TeleSpeech-ASR] CTC model|[Click me][wasm-hf-vad-asr-zh-telespeech]| [地址][wasm-ms-vad-asr-zh-telespeech]|
 |VAD + speech recognition (English + Chinese, 及多种中文方言) with Paraformer-large          |[Click me][wasm-hf-vad-asr-zh-en-paraformer-large]| [地址][wasm-ms-vad-asr-zh-en-paraformer-large]|
 |VAD + speech recognition (English + Chinese, 及多种中文方言) with Paraformer-small          |[Click me][wasm-hf-vad-asr-zh-en-paraformer-small]| [地址][wasm-ms-vad-asr-zh-en-paraformer-small]|
+|VAD + speech recognition (多语种及多种中文方言) with [Dolphin][Dolphin]-base          |[Click me][wasm-hf-vad-asr-multi-lang-dolphin-base]| [地址][wasm-ms-vad-asr-multi-lang-dolphin-base]|
 |Speech synthesis (English)                                                                  |[Click me][wasm-hf-tts-piper-en]| [地址][wasm-ms-tts-piper-en]|
 |Speech synthesis (German)                                                                   |[Click me][wasm-hf-tts-piper-de]| [地址][wasm-ms-tts-piper-de]|
 |Speaker diarization                                                                         |[Click me][wasm-hf-speaker-diarization]|[地址][wasm-ms-speaker-diarization]|
@@ -390,6 +391,10 @@ It uses TTS from sherpa-onnx. See also [✨ Speak command that uses the new glob
 [wasm-ms-vad-asr-zh-en-paraformer-large]: https://www.modelscope.cn/studios/k2-fsa/web-assembly-vad-asr-sherpa-onnx-zh-en-paraformer
 [wasm-hf-vad-asr-zh-en-paraformer-small]: https://huggingface.co/spaces/k2-fsa/web-assembly-vad-asr-sherpa-onnx-zh-en-paraformer-small
 [wasm-ms-vad-asr-zh-en-paraformer-small]: https://www.modelscope.cn/studios/k2-fsa/web-assembly-vad-asr-sherpa-onnx-zh-en-paraformer-small
+[Dolphin]: https://github.com/DataoceanAI/Dolphin
+[wasm-ms-vad-asr-multi-lang-dolphin-base]: https://modelscope.cn/studios/csukuangfj/web-assembly-vad-asr-sherpa-onnx-multi-lang-dophin-ctc
+[wasm-hf-vad-asr-multi-lang-dolphin-base]: https://huggingface.co/spaces/k2-fsa/web-assembly-vad-asr-sherpa-onnx-multi-lang-dophin-ctc
+
 [wasm-hf-tts-piper-en]: https://huggingface.co/spaces/k2-fsa/web-assembly-tts-sherpa-onnx-en
 [wasm-ms-tts-piper-en]: https://modelscope.cn/studios/k2-fsa/web-assembly-tts-sherpa-onnx-en
 [wasm-hf-tts-piper-de]: https://huggingface.co/spaces/k2-fsa/web-assembly-tts-sherpa-onnx-de

@@ -140,6 +140,20 @@ node ./test-offline-tts-vits-zh.js
 In the following, we demonstrate how to decode files and how to perform
 speech recognition with a microphone with `nodejs`.
 
+## ./test-offline-dolphin-ctc.js
+
+[./test-offline-dolphin-ctc.js](./test-offline-dolphin-ctc.js) demonstrates
+how to decode a file with a [Dolphin](https://github.com/DataoceanAI/Dolphin) CTC model.
+
+You can use the following command to run it:
+
+```bash
+wget -q https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+tar xvf sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+rm sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02.tar.bz2
+node ./test-offline-dolphin-ctc.js
+```
+
 ## ./test-offline-nemo-ctc.js
 
 [./test-offline-nemo-ctc.js](./test-offline-nemo-ctc.js) demonstrates

+// Copyright (c)  2025  Xiaomi Corporation (authors: Fangjun Kuang)
+//
+const fs = require('fs');
+const {Readable} = require('stream');
+const wav = require('wav');
+
+const sherpa_onnx = require('sherpa-onnx');
+
+function createOfflineRecognizer() {
+  let config = {
+    modelConfig: {
+      dolphin: {
+        model:
+            './sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/model.int8.onnx',
+      },
+      tokens:
+          './sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/tokens.txt',
+    }
+  };
+
+  return sherpa_onnx.createOfflineRecognizer(config);
+}
+
+const recognizer = createOfflineRecognizer();
+const stream = recognizer.createStream();
+
+const waveFilename =
+    './sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02/test_wavs/0.wav';
+const wave = sherpa_onnx.readWave(waveFilename);
+stream.acceptWaveform(wave.sampleRate, wave.samples);
+
+recognizer.decode(stream);
+const text = recognizer.getResult(stream).text;
+console.log(text);
+
+stream.free();
+recognizer.free();

@@ -197,6 +197,21 @@ def get_models():
             git diff
             """,
         ),
+        Model(
+            model_name="sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02",
+            hf="k2-fsa/web-assembly-vad-asr-sherpa-onnx-multi-lang-dophin-ctc",
+            ms="csukuangfj/web-assembly-vad-asr-sherpa-onnx-multi-lang-dophin-ctc",
+            short_name="vad-asr-multi_lang-dolphin_ctc",
+            cmd="""
+            pushd $model_name
+            mv model.int8.onnx ../dolphin.onnx
+            mv tokens.txt ../
+            popd
+            rm -rf $model_name
+            sed -i.bak 's%Zipformer%<a href="https://github.com/DataoceanAI/Dolphin">Dolphin</a> (多种中文方言及非常多种语言)%g' ../index.html
+            git diff
+            """,
+        ),
     ]
     return models
 

@@ -39,6 +39,10 @@ function freeConfig(config, Module) {
     freeConfig(config.fireRedAsr, Module)
   }
 
+  if ('dolphin' in config) {
+    freeConfig(config.dolphin, Module)
+  }
+
   if ('moonshine' in config) {
     freeConfig(config.moonshine, Module)
   }
@@ -562,6 +566,23 @@ function initSherpaOnnxOfflineNemoEncDecCtcModelConfig(config, Module) {
   }
 }
 
+function initSherpaOnnxOfflineDolphinModelConfig(config, Module) {
+  const n = Module.lengthBytesUTF8(config.model || '') + 1;
+
+  const buffer = Module._malloc(n);
+
+  const len = 1 * 4;  // 1 pointer
+  const ptr = Module._malloc(len);
+
+  Module.stringToUTF8(config.model || '', buffer, n);
+
+  Module.setValue(ptr, buffer, 'i8*');
+
+  return {
+    buffer: buffer, ptr: ptr, len: len,
+  }
+}
+
 function initSherpaOnnxOfflineWhisperModelConfig(config, Module) {
   const encoderLen = Module.lengthBytesUTF8(config.encoder || '') + 1;
   const decoderLen = Module.lengthBytesUTF8(config.decoder || '') + 1;
@@ -769,6 +790,12 @@ function initSherpaOnnxOfflineModelConfig(config, Module) {
     };
   }
 
+  if (!('dolphin' in config)) {
+    config.dolphin = {
+      model: '',
+    };
+  }
+
   if (!('whisper' in config)) {
     config.whisper = {
       encoder: '',
@@ -832,8 +859,12 @@ function initSherpaOnnxOfflineModelConfig(config, Module) {
   const fireRedAsr =
       initSherpaOnnxOfflineFireRedAsrModelConfig(config.fireRedAsr, Module);
 
+  const dolphin =
+      initSherpaOnnxOfflineDolphinModelConfig(config.dolphin, Module);
+
   const len = transducer.len + paraformer.len + nemoCtc.len + whisper.len +
-      tdnn.len + 8 * 4 + senseVoice.len + moonshine.len + fireRedAsr.len;
+      tdnn.len + 8 * 4 + senseVoice.len + moonshine.len + fireRedAsr.len +
+      dolphin.len;
 
   const ptr = Module._malloc(len);
 
@@ -932,10 +963,14 @@ function initSherpaOnnxOfflineModelConfig(config, Module) {
   Module._CopyHeap(fireRedAsr.ptr, fireRedAsr.len, ptr + offset);
   offset += fireRedAsr.len;
 
+  Module._CopyHeap(dolphin.ptr, dolphin.len, ptr + offset);
+  offset += dolphin.len;
+
   return {
     buffer: buffer, ptr: ptr, len: len, transducer: transducer,
         paraformer: paraformer, nemoCtc: nemoCtc, whisper: whisper, tdnn: tdnn,
-        senseVoice: senseVoice, moonshine: moonshine, fireRedAsr: fireRedAsr
+        senseVoice: senseVoice, moonshine: moonshine, fireRedAsr: fireRedAsr,
+        dolphin: dolphin
   }
 }
 

@@ -13,6 +13,7 @@ extern "C" {
 static_assert(sizeof(SherpaOnnxOfflineTransducerModelConfig) == 3 * 4, "");
 static_assert(sizeof(SherpaOnnxOfflineParaformerModelConfig) == 4, "");
 
+static_assert(sizeof(SherpaOnnxOfflineDolphinModelConfig) == 4, "");
 static_assert(sizeof(SherpaOnnxOfflineNemoEncDecCtcModelConfig) == 4, "");
 static_assert(sizeof(SherpaOnnxOfflineWhisperModelConfig) == 5 * 4, "");
 static_assert(sizeof(SherpaOnnxOfflineFireRedAsrModelConfig) == 2 * 4, "");
@@ -29,7 +30,8 @@ static_assert(sizeof(SherpaOnnxOfflineModelConfig) ==
                       sizeof(SherpaOnnxOfflineTdnnModelConfig) + 8 * 4 +
                       sizeof(SherpaOnnxOfflineSenseVoiceModelConfig) +
                       sizeof(SherpaOnnxOfflineMoonshineModelConfig) +
-                      sizeof(SherpaOnnxOfflineFireRedAsrModelConfig),
+                      sizeof(SherpaOnnxOfflineFireRedAsrModelConfig) +
+                      sizeof(SherpaOnnxOfflineDolphinModelConfig),
 
               "");
 static_assert(sizeof(SherpaOnnxFeatureConfig) == 2 * 4, "");
@@ -73,6 +75,7 @@ void PrintOfflineRecognizerConfig(SherpaOnnxOfflineRecognizerConfig *config) {
   auto sense_voice = &model_config->sense_voice;
   auto moonshine = &model_config->moonshine;
   auto fire_red_asr = &model_config->fire_red_asr;
+  auto dolphin = &model_config->dolphin;
 
   fprintf(stdout, "----------offline transducer model config----------\n");
   fprintf(stdout, "encoder: %s\n", transducer->encoder);
@@ -110,6 +113,9 @@ void PrintOfflineRecognizerConfig(SherpaOnnxOfflineRecognizerConfig *config) {
   fprintf(stdout, "encoder: %s\n", fire_red_asr->encoder);
   fprintf(stdout, "decoder: %s\n", fire_red_asr->decoder);
 
+  fprintf(stdout, "----------offline Dolphin model config----------\n");
+  fprintf(stdout, "model: %s\n", dolphin->model);
+
   fprintf(stdout, "tokens: %s\n", model_config->tokens);
   fprintf(stdout, "num_threads: %d\n", model_config->num_threads);
   fprintf(stdout, "provider: %s\n", model_config->provider);

@@ -73,48 +73,50 @@ function createOfflineRecognizerSenseVoice() {}
 
 function initOfflineRecognizer() {
   let config = {
-    modelConfig : {
-      debug : 1,
-      tokens : './tokens.txt',
+    modelConfig: {
+      debug: 1,
+      tokens: './tokens.txt',
     },
   };
   if (fileExists('sense-voice.onnx') == 1) {
     config.modelConfig.senseVoice = {
-      model : './sense-voice.onnx',
-      useInverseTextNormalization : 1,
+      model: './sense-voice.onnx',
+      useInverseTextNormalization: 1,
     };
   } else if (fileExists('whisper-encoder.onnx')) {
     config.modelConfig.whisper = {
-      encoder : './whisper-encoder.onnx',
-      decoder : './whisper-decoder.onnx',
+      encoder: './whisper-encoder.onnx',
+      decoder: './whisper-decoder.onnx',
     };
   } else if (fileExists('transducer-encoder.onnx')) {
     config.modelConfig.transducer = {
-      encoder : './transducer-encoder.onnx',
-      decoder : './transducer-decoder.onnx',
-      joiner : './transducer-joiner.onnx',
+      encoder: './transducer-encoder.onnx',
+      decoder: './transducer-decoder.onnx',
+      joiner: './transducer-joiner.onnx',
     };
     config.modelConfig.modelType = 'transducer';
   } else if (fileExists('nemo-transducer-encoder.onnx')) {
     config.modelConfig.transducer = {
-      encoder : './nemo-transducer-encoder.onnx',
-      decoder : './nemo-transducer-decoder.onnx',
-      joiner : './nemo-transducer-joiner.onnx',
+      encoder: './nemo-transducer-encoder.onnx',
+      decoder: './nemo-transducer-decoder.onnx',
+      joiner: './nemo-transducer-joiner.onnx',
     };
     config.modelConfig.modelType = 'nemo_transducer';
   } else if (fileExists('paraformer.onnx')) {
     config.modelConfig.paraformer = {
-      model : './paraformer.onnx',
+      model: './paraformer.onnx',
     };
   } else if (fileExists('telespeech.onnx')) {
     config.modelConfig.telespeechCtc = './telespeech.onnx';
   } else if (fileExists('moonshine-preprocessor.onnx')) {
     config.modelConfig.moonshine = {
-      preprocessor : './moonshine-preprocessor.onnx',
-      encoder : './moonshine-encoder.onnx',
-      uncachedDecoder : './moonshine-uncached-decoder.onnx',
-      cachedDecoder : './moonshine-cached-decoder.onnx'
+      preprocessor: './moonshine-preprocessor.onnx',
+      encoder: './moonshine-encoder.onnx',
+      uncachedDecoder: './moonshine-uncached-decoder.onnx',
+      cachedDecoder: './moonshine-cached-decoder.onnx'
     };
+  } else if (fileExists('dolphin.onnx')) {
+    config.modelConfig.dolphin = {model: './dolphin.onnx'};
   } else {
     console.log('Please specify a model.');
     alert('Please specify a model.');
@@ -133,7 +135,7 @@ Module.locateFile = function(path, scriptDirectory = '') {
 Module.setStatus = function(status) {
   console.log(`status ${status}`);
   const statusElement = document.getElementById('status');
-  if (status == "Running...") {
+  if (status == 'Running...') {
     status = 'Model downloaded. Initializing recongizer...'
   }
   statusElement.textContent = status;
@@ -170,11 +172,11 @@ if (navigator.mediaDevices.getUserMedia) {
   console.log('getUserMedia supported.');
 
   // see https://w3c.github.io/mediacapture-main/#dom-mediadevices-getusermedia
-  const constraints = {audio : true};
+  const constraints = {audio: true};
 
   let onSuccess = function(stream) {
     if (!audioCtx) {
-      audioCtx = new AudioContext({sampleRate : expectedSampleRate});
+      audioCtx = new AudioContext({sampleRate: expectedSampleRate});
     }
     console.log(audioCtx);
     recordSampleRate = audioCtx.sampleRate;
@@ -330,8 +332,9 @@ if (navigator.mediaDevices.getUserMedia) {
     };
   };
 
-  let onError = function(
-      err) { console.log('The following error occured: ' + err); };
+  let onError = function(err) {
+    console.log('The following error occured: ' + err);
+  };
 
   navigator.mediaDevices.getUserMedia(constraints).then(onSuccess, onError);
 } else {
@@ -387,7 +390,7 @@ function toWav(samples) {
     offset += 2;
   }
 
-  return new Blob([ view ], {type : 'audio/wav'});
+  return new Blob([view], {type: 'audio/wav'});
 }
 
 // this function is copied from